Python 3
x
import pandas as pddata = pd.read_csv(r"ipl.csv",encoding = "ISO-8859-1")data.head()data = data[:99]# print(data)# data.isnull().sum()import seaborn as sns# data.corr()x
import plotly.offline as poimport plotly.express as pxpx.scatter(data_frame=data,x=data['Inns'],y=data['Runs'],color=data['PLAYER'])Signature: px.scatter( data_frame=None, x=None, y=None, color=None, symbol=None, size=None, hover_name=None, hover_data=None, custom_data=None, text=None, facet_row=None, facet_col=None, facet_col_wrap=0, facet_row_spacing=None, facet_col_spacing=None, error_x=None, error_x_minus=None, error_y=None, error_y_minus=None, animation_frame=None, animation_group=None, category_orders={}, labels={}, orientation=None, color_discrete_sequence=None, color_discrete_map={}, color_continuous_scale=None, range_color=None, color_continuous_midpoint=None, symbol_sequence=None, symbol_map={}, opacity=None, size_max=None, marginal_x=None, marginal_y=None, trendline=None, trendline_color_override=None, log_x=False, log_y=False, range_x=None, range_y=None, render_mode='auto', title=None, template=None, width=None, height=None, ) Docstring: In a scatter plot, each row of `data_frame` is represented by a symbol mark in 2D space. Parameters ---------- data_frame: DataFrame or array-like or dict This argument needs to be passed for column names (and not keyword names) to be used. Array-like and dict are tranformed internally to a pandas DataFrame. Optional: if missing, a DataFrame gets constructed under the hood using the other arguments. x: str or int or Series or array-like Either a name of a column in `data_frame`, or a pandas Series or array_like object. Values from this column or array_like are used to position marks along the x axis in cartesian coordinates. Either `x` or `y` can optionally be a list of column references or array_likes, in which case the data will be treated as if it were 'wide' rather than 'long'. y: str or int or Series or array-like Either a name of a column in `data_frame`, or a pandas Series or array_like object. Values from this column or array_like are used to position marks along the y axis in cartesian coordinates. Either `x` or `y` can optionally be a list of column references or array_likes, in which case the data will be treated as if it were 'wide' rather than 'long'. color: str or int or Series or array-like Either a name of a column in `data_frame`, or a pandas Series or array_like object. Values from this column or array_like are used to assign color to marks. symbol: str or int or Series or array-like Either a name of a column in `data_frame`, or a pandas Series or array_like object. Values from this column or array_like are used to assign symbols to marks. size: str or int or Series or array-like Either a name of a column in `data_frame`, or a pandas Series or array_like object. Values from this column or array_like are used to assign mark sizes. hover_name: str or int or Series or array-like Either a name of a column in `data_frame`, or a pandas Series or array_like object. Values from this column or array_like appear in bold in the hover tooltip. hover_data: list of str or int, or Series or array-like, or dict Either a list of names of columns in `data_frame`, or pandas Series, or array_like objects or a dict with column names as keys, with values True (for default formatting) False (in order to remove this column from hover information), or a formatting string, for example ':.3f' or '|%a' or list-like data to appear in the hover tooltip or tuples with a bool or formatting string as first element, and list-like data to appear in hover as second element Values from these columns appear as extra data in the hover tooltip. custom_data: list of str or int, or Series or array-like Either names of columns in `data_frame`, or pandas Series, or array_like objects Values from these columns are extra data, to be used in widgets or Dash callbacks for example. This data is not user-visible but is included in events emitted by the figure (lasso selection etc.) text: str or int or Series or array-like Either a name of a column in `data_frame`, or a pandas Series or array_like object. Values from this column or array_like appear in the figure as text labels. facet_row: str or int or Series or array-like Either a name of a column in `data_frame`, or a pandas Series or array_like object. Values from this column or array_like are used to assign marks to facetted subplots in the vertical direction. facet_col: str or int or Series or array-like Either a name of a column in `data_frame`, or a pandas Series or array_like object. Values from this column or array_like are used to assign marks to facetted subplots in the horizontal direction. facet_col_wrap: int Maximum number of facet columns. Wraps the column variable at this width, so that the column facets span multiple rows. Ignored if 0, and forced to 0 if `facet_row` or a `marginal` is set. facet_row_spacing: float between 0 and 1 Spacing between facet rows, in paper units. Default is 0.03 or 0.0.7 when facet_col_wrap is used. facet_col_spacing: float between 0 and 1 Spacing between facet columns, in paper units Default is 0.02. error_x: str or int or Series or array-like Either a name of a column in `data_frame`, or a pandas Series or array_like object. Values from this column or array_like are used to size x-axis error bars. If `error_x_minus` is `None`, error bars will be symmetrical, otherwise `error_x` is used for the positive direction only. error_x_minus: str or int or Series or array-like Either a name of a column in `data_frame`, or a pandas Series or array_like object. Values from this column or array_like are used to size x-axis error bars in the negative direction. Ignored if `error_x` is `None`. error_y: str or int or Series or array-like Either a name of a column in `data_frame`, or a pandas Series or array_like object. Values from this column or array_like are used to size y-axis error bars. If `error_y_minus` is `None`, error bars will be symmetrical, otherwise `error_y` is used for the positive direction only. error_y_minus: str or int or Series or array-like Either a name of a column in `data_frame`, or a pandas Series or array_like object. Values from this column or array_like are used to size y-axis error bars in the negative direction. Ignored if `error_y` is `None`. animation_frame: str or int or Series or array-like Either a name of a column in `data_frame`, or a pandas Series or array_like object. Values from this column or array_like are used to assign marks to animation frames. animation_group: str or int or Series or array-like Either a name of a column in `data_frame`, or a pandas Series or array_like object. Values from this column or array_like are used to provide object-constancy across animation frames: rows with matching `animation_group`s will be treated as if they describe the same object in each frame. category_orders: dict with str keys and list of str values (default `{}`) By default, in Python 3.6+, the order of categorical values in axes, legends and facets depends on the order in which these values are first encountered in `data_frame` (and no order is guaranteed by default in Python below 3.6). This parameter is used to force a specific ordering of values per column. The keys of this dict should correspond to column names, and the values should be lists of strings corresponding to the specific display order desired. labels: dict with str keys and str values (default `{}`) By default, column names are used in the figure for axis titles, legend entries and hovers. This parameter allows this to be overridden. The keys of this dict should correspond to column names, and the values should correspond to the desired label to be displayed. orientation: str, one of `'h'` for horizontal or `'v'` for vertical. (default `'v'` if `x` and `y` are provided and both continous or both categorical, otherwise `'v'`(`'h'`) if `x`(`y`) is categorical and `y`(`x`) is continuous, otherwise `'v'`(`'h'`) if only `x`(`y`) is provided) color_discrete_sequence: list of str Strings should define valid CSS-colors. When `color` is set and the values in the corresponding column are not numeric, values in that column are assigned colors by cycling through `color_discrete_sequence` in the order described in `category_orders`, unless the value of `color` is a key in `color_discrete_map`. Various useful color sequences are available in the `plotly.express.colors` submodules, specifically `plotly.express.colors.qualitative`. color_discrete_map: dict with str keys and str values (default `{}`) String values should define valid CSS-colors Used to override `color_discrete_sequence` to assign a specific colors to marks corresponding with specific values. Keys in `color_discrete_map` should be values in the column denoted by `color`. Alternatively, if the values of `color` are valid colors, the string `'identity'` may be passed to cause them to be used directly. color_continuous_scale: list of str Strings should define valid CSS-colors This list is used to build a continuous color scale when the column denoted by `color` contains numeric data. Various useful color scales are available in the `plotly.express.colors` submodules, specifically `plotly.express.colors.sequential`, `plotly.express.colors.diverging` and `plotly.express.colors.cyclical`. range_color: list of two numbers If provided, overrides auto-scaling on the continuous color scale. color_continuous_midpoint: number (default `None`) If set, computes the bounds of the continuous color scale to have the desired midpoint. Setting this value is recommended when using `plotly.express.colors.diverging` color scales as the inputs to `color_continuous_scale`. symbol_sequence: list of str Strings should define valid plotly.js symbols. When `symbol` is set, values in that column are assigned symbols by cycling through `symbol_sequence` in the order described in `category_orders`, unless the value of `symbol` is a key in `symbol_map`. symbol_map: dict with str keys and str values (default `{}`) String values should define plotly.js symbols Used to override `symbol_sequence` to assign a specific symbols to marks corresponding with specific values. Keys in `symbol_map` should be values in the column denoted by `symbol`. Alternatively, if the values of `symbol` are valid symbol names, the string `'identity'` may be passed to cause them to be used directly. opacity: float Value between 0 and 1. Sets the opacity for markers. size_max: int (default `20`) Set the maximum mark size when using `size`. marginal_x: str One of `'rug'`, `'box'`, `'violin'`, or `'histogram'`. If set, a horizontal subplot is drawn above the main plot, visualizing the x-distribution. marginal_y: str One of `'rug'`, `'box'`, `'violin'`, or `'histogram'`. If set, a vertical subplot is drawn to the right of the main plot, visualizing the y-distribution. trendline: str One of `'ols'` or `'lowess'`. If `'ols'`, an Ordinary Least Squares regression line will be drawn for each discrete-color/symbol group. If `'lowess`', a Locally Weighted Scatterplot Smoothing line will be drawn for each discrete-color/symbol group. trendline_color_override: str Valid CSS color. If provided, and if `trendline` is set, all trendlines will be drawn in this color. log_x: boolean (default `False`) If `True`, the x-axis is log-scaled in cartesian coordinates. log_y: boolean (default `False`) If `True`, the y-axis is log-scaled in cartesian coordinates. range_x: list of two numbers If provided, overrides auto-scaling on the x-axis in cartesian coordinates. range_y: list of two numbers If provided, overrides auto-scaling on the y-axis in cartesian coordinates. render_mode: str One of `'auto'`, `'svg'` or `'webgl'`, default `'auto'` Controls the browser API used to draw marks. `'svg`' is appropriate for figures of less than 1000 data points, and will allow for fully-vectorized output. `'webgl'` is likely necessary for acceptable performance above 1000 points but rasterizes part of the output. `'auto'` uses heuristics to choose the mode. title: str The figure title. template: str or dict or plotly.graph_objects.layout.Template instance The figure template name (must be a key in plotly.io.templates) or definition. width: int (default `None`) The figure width in pixels. height: int (default `None`) The figure height in pixels. Returns ------- plotly.graph_objects.Figure File: c:\users\lenovo\anaconda3\lib\site-packages\plotly\express\_chart_types.py Type: function